ArcelorMittal Taps AWS to Automate Global Steel Operations

ArcelorMittal on Monday said it has partnered with Amazon Web Services to automate its global operations, bringing cloud and AI capabilities directly into its steelmaking and mining processes.

The collaboration places AWS infrastructure at the edge of ArcelorMittal's production environments, converging operational technology and information technology on a single platform designed for security and scale. The company plans to use AWS services for industrial IoT, real-time sensor data and machine learning to deploy predictive maintenance, computer-vision quality control and digital twins of physical assets and production lines.

The shift is meant to improve safety, asset reliability and energy efficiency. AWS will also design and deliver a training programme for ArcelorMittal's global workforce to accelerate digital and AI adoption.

“By converging our operational and information technology on a single secure platform, we are moving to digitally enabled operations – safer for our people, more reliable in output, and more sustainable by design. This is how we industrialise AI at scale across the steelmaking value chain,” said Nik Puri, Group CIO & CISO at ArcelorMittal.

For the steel sector, the partnership signals that large integrated producers are willing to trust cloud-native architectures for real-time control of heavy industrial processes. ArcelorMittal operates primary steelmaking in 14 countries and across 60 markets. Its move to run predictive analytics and vision systems on AWS rather than on-premise programmable logic controllers could pressure peers like Nippon Steel, POSCO and Tata Steel to accelerate their own OT-IT convergence plans, particularly if ArcelorMittal reports measurable gains in uptime or defect reduction.

The steel industry has traditionally been slow to adopt cloud at the plant-floor level, citing latency, security and the high cost of retrofitting legacy equipment. ArcelorMittal's approach–using edge computing to process sensor data close to the blast furnace while still feeding aggregated data to AWS for model training–tries to solve that tension. Competitors with similar scale and capital budgets may find it harder to justify staying on isolated on-premise systems once a proof of concept at ArcelorMittal shows results.

ArcelorMittal did not disclose financial terms of the agreement or a timeline for full deployment. The company said the education programme would cover machine learning, data engineering and cloud architecture for its technical workforce.